DocumentCode :
41520
Title :
The MS2DB {++} Webserver: Disulfide Bond Determination Through Evidence Combination
Author :
Murad, W. ; Singh, Rajdeep
Author_Institution :
Dept. of Comput. Sci., San Francisco State Univ., San Francisco, CA, USA
Volume :
12
Issue :
4
fYear :
2013
fDate :
Dec. 2013
Firstpage :
340
Lastpage :
342
Abstract :
MS2DB ++ is a web server for computationally determining disulfide connectivity in proteins by combining evidence from multiple methods. The constituent methods implemented as part of the MS2DB ++ webserver include a mass spectrometry-based method and two protein sequence-based predictive methods. The software also allows users to incorporate results from up to two other external methods of choice. The results from all these methods are combined using Dempster-Shafer theory through the use of four different formulations for evidence combination. In practice, MS2DB ++ can be especially helpful in obtaining the disulfide topology in cases where no single method performs consistently across a set of molecules due to complexity of the bonding topology, specificities of the fragmentation pattern, or limitations of computational models.
Keywords :
Internet; biology computing; file servers; mass spectroscopic chemical analysis; proteins; proteomics; Dempster-Shafer theory; MS2DB ++ webserver; bonding topology complexity; computational model limitations; constituent methods; disulfide bond determination; disulfide connectivity; disulfide topology; evidence combination; external methods; fragmentation pattern; mass spectrometry-based method; multiple methods; protein sequence-based predictive method; Biology computing; Decision support systems; Mass spectroscopy; Prediction methods; Proteomics; Support vector machines; , proteomics; Biology computing; decision support systems; disulfide bonds; mass spectrometry; prediction methods;
fLanguage :
English
Journal_Title :
NanoBioscience, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1241
Type :
jour
DOI :
10.1109/TNB.2013.2289391
Filename :
6695758
Link To Document :
بازگشت